Cloud and precipitation processes remain among the largest sources of uncertainties in weather and climate modeling, affecting estimates of both greenhouse-gas-driven climate change and aerosol forcing. Substantial progress has been made in recent years in observing (satellite, in-situ and ground-based) and modeling of these processes. In this session, we solicit presentations that advance process understanding of cloud and precipitation physics and their representation in weather and climate models using observations and modeling. This includes innovative use of observations and high-resolution modeling to diagnose key aspects of physical processes; it also includes applying process-oriented analysis to evaluate, constrain and improve cloud and precipitation parameterizations. Presentations on how process-based constraints on model physics improve our understanding of climate feedback and aerosol forcing are encouraged. The use of satellite simulators as tools to make scale-aware and definition-aware comparisons of models and observations is welcomed.